Analysing, Interpreting, and Testing the Invariance of the Actor-Partner Interdependence Model

Abstract

Although in recent years researchers have begun to utilize dyadic data analyses such as the actor-partner interdependence model (APIM), certain limitations to the applicability of these models still exist. Given the complexity of APIMs, most researchers will often use observed scores to estimate the model's parameters, which can significantly limit and underestimate statistical results. The aim of this article is to highlight the importance of conducting a confirmatory factor analysis (CFA) of equivalent constructs between dyad members (i.e. measurement equivalence/invariance; ME/I). Different steps for merging CFA and APIM procedures will be detailed in order to shed light on new and integrative methods.

A longitudinal application of the Actor Partner Interdependence Model extended Mediations to the health effects of dyadic support

“…With this model, it is possible to estimate the direct and indirect effects of X on Y through one or more mediator (M) when M is measured for both members of the dyad. Essentially, four different effects could be estimated [30,31]: two actor effects (i.e., one for husband and one for wife) and two partner effects (i.e., one for husband and one for wife). In this case, the indirect effects are of central importance, as they quantify and convey information about the mechanism by which X is connected to Y, and in line with this model, the mechanisms could operate through the person's own M, the partner's M, or both simultaneously.…”

The Actor-Partner Interdependence Model in the Study of Aggression and Victimization within Couples: An Empirical Examination in 361 Dyads

“…The likelihood ratio test (LRT) allows for comparison of more restricted models with less restricted models. Given that dyads were considered distinguishable (one male and one female member), standard procedures used in previous studies were followed in this analysis (Gareau et al, 2016).…”

Assessing the effect of child’s gender on their father–mother perception of the PedsQL™ 4.0 questionnaire: an iterative hybrid ordinal logistic regression/item response theory approach with Monte Carlo simulation

“…However, some other DIF detection techniques were introduced which could deal with this problem and model the between groups covariance. The actor–partner interdependence models [ 39 , 40 ] and the longitudinal factor analysis based-models [ 41 ], which are tested measurement invariance over the time, are among these methods. Nonetheless, none of these methods could provide a simulation-based mechanism to evaluate statistical criteria for detecting DIF.…”